Catálogo de publicaciones - libros

XML queries are often expanded based on ontology for broad and in-depth search. But, queries generated from ontology itself are not specific to target documents. Accordingly, the overall search efficiency will deteriorate with those superfluous queries that are not succinct to the target. We suggest an ontology reduction algorithm where the target DTD is matched to ontology such that queries can be minimally expanded. The matched and reduced ontology is successively reusable for the document of a kind. This target-fitted query expansion method is expected to be more efficient than conventional methods in query processing.

This paper proposes a non-deterministic event correlation technique for diagnosis problem of end-to-end service in network, which uses an event –fault model based on path domain of events. The technique utilizes a refined heuristic approach to create and update fault hypotheses that can explain these events received by system, and computes these hypotheses’ belief by C-F model method. The result of event correlation is the hypothesis with maximum belief. Simulation shows this approach can get a high accuracy even in the case of low observability events ratio.

The Systems Biology Markup Language(SBML) is an XML-based format for representing models of Systems Biology. BioSPI is a formal model to simulate biological systems, which is evolved from process calculi. Based on the previous research on modeling Systems Biology using process algebra, we propose a method to map SBML to BioSPI. The motivation of the work is to make full use of BioSPI to analyze biological systems described by SBML. In this paper, the mapping rules are presented and an example is given to show the simulation results.

Web-based information portals provide a point of access onto an integrated and structured body of information about some domain. Knowledge portals are information portals, which make an important contribution to enabling enterprise knowledge management by providing users with a consolidated, personalized user interface that allows efficient access to various types of information. Portlets are mainly ways to present contents in knowledge portals. They are a group of components, which can be involved by a portal container. However, there are lacks no interaction between those portlets. This paper discusses information integration aspects within knowledge portals and presents an approach for communicating the user context (revealing the user’s information need) among portlets, utilizing ontologies technologies.

In this paper, we propose a novel wavelet transform based on the polar coordinates for datamining applications. In general, the Harr wavelet transform has been popularly used for data decomposition. However, the Harr wavelet transform shows the poor performance for the locally distributed data which are clustered around certain values, since it uses the averages as representatives for data decomposition. The proposed wavelet transform is based on the the polar coordinates which is not affected by the averages and is more suitable than the Harr wavelet transform for data decomposition of the locally distributed data.

In this paper, we develop a security design metric that can be used at system design time to build more secure systems. This metric is based on the system-wide approach and adopt a reliability model and scenario testing technique to produce a feedback cycle.

Core operations (e.g. TDMA scheduler, synchronized sleep period, data aggregation) of many proposed protocols for different layer of sensor network necessitate clock synchronization. Our paper mingles the scheme of dynamic clustering and diffusion based asynchronous averaging algorithm for clock synchronization in sensor network. Our proposed algorithm takes the advantage of dynamic clustering and then applies asynchronous averaging algorithm for synchronization to reduce number of rounds and operations required for converging time which in turn save energy significantly than energy required in diffusion based asynchronous averaging algorithm.

In this paper, an intelligent power management scheme for embedded systems with wireless applications is proposed to reduce the power consumption of the overall system. The proposed method is based on the feedback of the extreme channel state indicator that is designed to detect the extremely bad channel condition. The considerable power reduction is achieved by turning off modules within the embedded system related to the information transmissions under such an unreliable channel condition. A simple extreme channel state detector is also proposed.

Siguo game is an interesting test-bed for artificial intelligent research. It is a game of imperfect information, where completing players must deal with possible knowledge, risk assessment, and possible deception and leaguing players have to deal with cooperation and information signal transmission. Since Siguo game is imperfect information game that the player doesn’t know the type of piece and strategy that opponent moves, to exactly guess type of opponent’ piece is a very important parameter to evaluate the capability of Siguo game program. In this paper, we first construct a fuzzy type table by analyzing more than one thousand different embattle lineups (i.e. chess manuals) of Siguo game, and then we present a algorithm that updates type table by using information from opponent during playing game. The updating type of pieces algorithm is designed by considering the two strategies, i.e. optimism and pessimism based on the fuzzy notion. At last we give a method to guess the type of piece by using fuzzy type proximity relation between two neighboring pieces.

The large-scale genome-wide SNP data being acquired from biomedical domains have offered resources to evaluate modern data mining techniques in applications to genetic studies. The purpose of this study is to extend our recently developed gene mining approach to extracting the relevant SNPs for alcoholism using sib-pair IBD profiles of pedigrees. Application to a publicly available large dataset of 100 simulated replicates for three American populations demonstrates that the proposed ensemble decision approach has successfully identified most of the simulated true loci, thus implicating that IBD statistic could be used as one of the informatics for mining the genetic underpins for complex human diseases.